Privacy Heroes Need Data Disguises
Privacy Heroes Need Data Disguises
复制标题
隐私英雄需要数据伪装
DOI：
10.1145/3458336.3465284
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Kohler, Eddie
中科院分区：
文献类型：
--
作者：
Tsai, Lillian;Schwarzkopf, Malte;Kohler, Eddie
在复杂、数据丰富的应用程序中提供隐私是很困难的。删除帐户、匿名帐户的贡献以及其他与隐私相关的操作可能需要遍历和转换关系数据库中的交织状态。找到受影响的数据已经不是一件容易的事，但隐私行动还必须平衡相互竞争的要求，例如出于法律原因保留数据踪迹或允许用户改变主意。我们相信，用于指定和实施隐私转换的系统共享框架可以简化和增强应用程序。我们的原型数据伪装支持细粒度、细微差别和有用的策略，手动实现这些策略会很麻烦，包括可以组合的可逆转换。
Providing privacy in complex, data-rich applications is hard. Deleting accounts, anonymizing an account's contributions, and other privacy-related actions may require the traversal and transformation of interwoven state in a relational database. Finding the affected data is already nontrivial, but privacy actions must additionally balance competing requirements, such as preserving data trails for legal reasons or allowing users to change their mind. We believe a systematic shared framework for specifying and implementing privacy transformations could simplify and empower applications. Our prototype,data disguising, supports fine-grained, nuanced, and useful policies that would be cumbersome to implement manually, including reversible transformations that can compose.